There is a flurry of excitement about Enterprise Manager 13c and I’m blown away by how many customers are looking not just to install and test out the new release, but have plans already underway to upgrade to it.

This post is heavily inspired by the events of #RIPTwitter and the recent Fine Brothers fiasco, but it could apply to just about any company, product or person. When I say user base, I could easily mean customers or fan base.

The following is probably only relevant for customers that run Oracle on big servers with lots of cores in single instance mode (this specific problem here doesn't reproduce in a RAC environment, see below for an explanation why), like one of my clients that makes use of the Exadata Xn-8 servers, for example a X4-8 with 120 cores / 240 CPUs per node (but also reproduced on older and smaller boxes with 64 cores / 128 CPUs per node).

The intention of this blogpost is to show the Oracle wait time granularity and the Oracle database time measurement granularity. One of the reasons for doing this, is the Oracle database switched from using the function gettimeofday() up to version 11.2 to clock_gettime() to measure time.

This switch is understandable, as gettimeofday() is a best guess of the kernel of the wall clock time, while clock_gettime(CLOCK_MONOTONIC,…) is an monotonic increasing timer, which means it is more precise and does not have the option to drift backward, which gettimeofday() can do in certain circumstances, like time adjustments via NTP.

The first thing I wanted to proof, is the switch of the gettimeofday() call to the clock_gettime() call. This turned out not to be as simple as I thought.

A few months ago I wrote about an exciting product that allows you to achieve no data loss in a disaster even without using the maximum protection Data Guard that relies on super expensive synchronous networks. Recently I had a chance to actually work on that system and replicate the scenarios. Here I explain how that actually works, with commands and actual outputs.

Database performance is in my jeans. Not my genes, I really do mean my jeans – an old pair of denim trousers. I look at my tatty attire keeping my legs warm and it reminds me of Oracle database performance.

A recent posting on OTN presented a performance anomaly when comparing a parallel “insert /*+ append */” with a parallel “create table as select”. The CTAS statement took about 4 minutes, the insert about 45 minutes. Since the process of getting the data into the data blocks would be the same in both cases something was clearly not working properly. Following Occam’s razor, the first check had to be the execution plans – when two statements that “ought” to do the same amount of work take very different times it’s probably something to do with the execution plans – so here are the two statements with their plans: